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Chemical Reaction Neural Network

Home Page: https://arxiv.org/abs/2002.09062

License: MIT License

Julia 97.94% Python 2.06%
neural-ode sciml chemical-kinetics

crnn's Issues

Ideas on training CRNN from experimental data

It would be nice to study a case with experimental data. The chemical kinetic model can be very simple, although. It would be useful when you show something to others.

Maybe Ritaank and Matthew can help with it. I will also make up some candidates on this issue.

Query in robertsons code in predict_neuralode function

Hi @jiweiqi ,In robertson's code.. shouldn't one solve for _prob and not prob .. copying here code for the reference from
https://github.com/DENG-MIT/CRNN/blob/main/robertson/rober_crnn.jl

function predict_neuralode(u0, p; sample = datasize)
    global w_in, w_b, w_out = p2vec(p)
    _prob = remake(prob, tspan=[0, tsteps[sample]])                               # this line
    sol = solve(prob, alg, u0=u0, p=p, saveat=tsteps[1:sample],             # this line
                sensalg=sense, verbose=false, maxiters=maxiters)

``

Guidelines for bounds on clamping weights , scaling derivatives and slope

Opening issue for bit detailed documentation on

  • slope,
  • scaling dydt,
  • bounds on clamping weights, scaling weights
  • scaling loss by the standard deviation
  • sensealg for different cases (stiff and non-stiff)
  • when to bother about g_norm or gradient in the training process(like we don't bother much in simple case 1)
  • tanh vs gelu ? Comments on different activations in different cases

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